| --- |
| dataset_info: |
| features: |
| - name: id |
| dtype: string |
| - name: dataset |
| dtype: string |
| - name: question |
| dtype: string |
| - name: options |
| sequence: string |
| - name: answer |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 2268293 |
| num_examples: 10687 |
| download_size: 1254741 |
| dataset_size: 2268293 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| This dataset was constructed as part of the EPFL Modern NLP (MNLP) course project to train and evaluate large language models on **multiple-choice question answering (MCQA)** tasks focused on scientific reasoning. |
|
|
| It aggregates and reformats **10,687 unique examples** from five high-quality academic and biomedical QA datasets, applying consistent structure, question normalization, and cross-source deduplication. |
|
|
| ### 📊 Dataset Composition |
|
|
| | Source Dataset | Link | Questions Used | Description | |
| |----------------|------|----------------|-------------| |
| | ARC-Challenge | [ai2_arc](https://huggingface.co/datasets/ai2_arc) | 1,119 | Harder science exam questions requiring multi-step reasoning | |
| | ARC-Easy | [ai2_arc](https://huggingface.co/datasets/ai2_arc) | 2,251 | Simpler science questions at the elementary/middle school level | |
| | QASC | [qasc](https://huggingface.co/datasets/qasc) | 3,000 (subset) | A filtered and deduplicated subset of the QASC dataset, which was originally larger (~8,000+ examples). Only 3,000 unique and diverse questions were selected for balance | |
| | OpenBookQA | [openbookqa](https://huggingface.co/datasets/openbookqa) | 3,317 | 4-option science questions, filtered to keep `humanScore ≥ 1` | |
| | PubMedQA | [pubmed_qa](https://huggingface.co/datasets/pubmed_qa) | 1,000 | Biomedical questions with Yes/No/Maybe answers based on PubMed abstracts | |
|
|
| ### 🧪 Preprocessing Pipeline |
|
|
| - **Normalization**: All questions were lowercased and stripped of whitespace for consistency. |
| - **Deduplication**: Each question was hashed (`md5(lowercase question)`) to detect and eliminate duplicates across datasets. |
| - **Filtering**: |
| - OpenBookQA was filtered to retain only questions with `humanScore ≥ 1`. |
| - PubMedQA was filtered to retain only labeled questions with answers in {yes, no, maybe}. |
| - QASC was **sampled and capped** at 3,000 unique questions to ensure dataset balance. |
| - **Unified formatting**: All entries follow the same JSON schema across sources. |
|
|
| ### 📦 Format |
|
|
| Each sample follows this structure: |
|
|
| ```json |
| { |
| "id": "qasc_481", |
| "dataset": "qasc", |
| "question": "What do bees use to make honey?", |
| "options": ["nectar", "pollen", "water", "leaves"], |
| "answer": "A" |
| } |
| |
| |
